Performance Testing

What Is Performance Testing?

Performance testing evaluates how a software system behaves under expected and extreme workloads. It focuses on speed, scalability, stability, and responsiveness, ensuring the system can handle real-world usage without degrading or failing.

Performance testing answers questions such as:

• How fast does the system respond?
• How many users can it support?
• Does performance degrade over time?
• What happens during peak usage?

Why It Matters	Who Performs It	When It Occurs
Prevents system slowdowns and outages Protects user experience and business reputation Ensures systems scale as usage grows Identifies bottlenecks before production Reduces costly emergency fixes after release A system that works functionally but performs poorly will quickly lose users.	Performance test engineers Developers (for tuning and diagnostics)	After system integration Before major releases Before go-live or high-traffic events After infrastructure or configuration changes Continuously for high-availability systems

Typical Performance Testing Techniques

1. Load Testing
   • Measures system behavior under expected user load.
   • Purpose: Confirm the system performs well under normal conditions.
   • Examples:
     • 1,000 concurrent users submitting transactions
     • Typical daily transaction volume
2. Stress Testing
   • Pushes the system beyond normal limits to identify breaking points.
   • Purpose: Understand system failure behavior and recovery.
   • Examples:
     • Sudden spike in users
     • Resource exhaustion scenarios
3. Scalability Testing
   • Evaluates how well the system scales when resources or users increase.
   • Purpose: Ensure growth does not degrade performance.
   • Examples:
     • Adding servers to handle more users
     • Cloud auto-scaling validation
4. Endurance (Soak) Testing
   • Runs the system under load for an extended period.
   • Purpose: Detect memory leaks and resource degradation.
   • Example:
     • 24-hour or multi-day sustained usage
5. Volume Testing
   • Tests system behavior with large amounts of data.
   • Purpose: Validate performance with high data volumes.
   • Examples:
     • Millions of records in a database
     • Large file uploads
6. Spike Testing
   • Introduces sudden, extreme load changes.
   • Purpose: Evaluate resilience during traffic surges.

Key Takeaways

• Performance testing validates speed, stability, and scalability
• Must reflect real-world usage patterns
• Should be performed before production, not after
• Needed for both SaaS platforms and custom systems where high-volume critical business processes exist